Robots made by Artists

Robots have been always made by computer scientists and mathematicians, but what would the Artificial Intelligence be like if it was made by an artist. This robot has a soul, and its risk-taking, adventurous, improvisational characteristics contrast the commonplace planning and analytical robot. Guy Hoffman, an animator and actor, worked on getting robots to collaborate with humans, especially through music. Hoffman’s robot can improvise with jazz musicians, and even head bob to rappers.

Guy Hoffman’s TED talk: http://www.youtube.com/watch?v=utV1sdjr4PY

Artificially Intelligent bots can see the Future

Alpha Beta Pruning is a widely used concept for computer players in two player games, such as Tic Tac Toe or Chess. It gives computers the ability to make very intelligent moves by anticipating future gameplay.

First, the computer player creates a decision tree of future possible moves made by the computer and its opponent. Alpha beta pruning uses the minimax algorithm to expediently search through the decision tree for the most intelligent future course of moves. The minimax algorithm assumes that the opponent will try to minimize the computer’s chance of winning and the computer player will try to maximize it (a fair assumption). Therefore, using this algorithm, the computer anticipates the opponents moves and is able to choose the path to maximize its score. The pruning algorithm expedites the search process by weeding out branches of the decision tree that would not occur according to the minimax algorithm assumption.

This ability gives computer players a sense of foresight in games and allows them to be a worthy adversary for human players.

Helpful links to learn more:

https://en.wikipedia.org/wiki/Monte_Carlo_method#Artificial_intelligence_for_games

https://en.wikipedia.org/wiki/Minimax#Minimax_algorithm_with_alternate_moves

EPGY Book Proposition

Inside Case-Based Reasoning (Artificial Intelligence Series)

I would greatly benefit by having this book for my final project because of its comprehensive and in depth explanation and insights into the field of case based reasoning. It even provides Lisp programming exercises to improve my skills in case based programming applications. By helping me by this book, my instructor will be able to gain repute since my project will yield a lot of publicity and ROI (return on investment) if I have this book. I will even cover a portion  of the book’s cost, so it’s the best deal in town!

http://www.amazon.com/Inside-Case-Based-Reasoning-Artificial-Intelligence/dp/0898597676/ref=sr_1_10?s=books&ie=UTF8&qid=1374873138&sr=1-10&keywords=case+based+reasoning

Shout out to my instructor, Sherol Chen, for giving us an opportunity to buy books for our final project.

2013 IEEE Big Data Conference

The IEEE Big Data Conference will meet in Santa Clara Hyatt in California from October 6-9, 2013. Their topics include big data mining, searches, security, and several others (for more, see: http://www.ischool.drexel.edu/bigdata/bigdata2013/topics.htm). I am interested in the International Workshop on Intelligent Agents for Big Data. This workshop will correlates with my current project in analyzing large amounts of data to make a computer bot capable of learning from its experiences. Overall, this conference addresses my interests in databases and artificial intelligence.

What is artificial intelligence?

Artificial intelligence is essentially Machine Thinking. It is a concept where machines, instead of being slaves of their human masters, will begin to coexist with humans as intelligent beings. Machines will not only be able to make an apt assessment of their environment, but also manipulate their environment according to their needs. Artificial intelligence is primarily making machines inherit human capabilities.

The conundrum for programmers is trying to get the computer to learn the proper strategies and correct moves. We don’t want to use an algorithm that just spoon-feeds the AI bot with the right answer easily. There has to be a balance of autonomy and guidance that us programmers have to give to our creations. Therefore, the AI bot will be flexible and perpetually improving.

The Future of the Surveillance Society

The NSA could provide a comprehensive insight on events across the country and can provide justice for the citizens. Yet, this power can abuse the people’s rights to privacy. Giving an organization an unknown amount of agency is a horrifying reality. Therefore, I believe we should entrust the surveillance society with an artificially intelligent system of bots that will be autonomous and extract only necessary information. In the end, an amount of privacy must be sacrificed to ensure justice across the country. The bots’ functions will be broadcasted publicly so that the citizens are aware of the good intentions of NSA.

Engineer, Artist, Scientist, Educator – Who am I? Where am I headed?

I’m not bounded by these labels of engineer, artist, scientist, and educator, yet my qualities make me more like some of the above than the others. My inability to sit still without wanting to help people around me and learn from what others are doing makes me a dynamic person with a focus on optimization. My bent towards examples and products rather than theory (though theory is quite intriguing) makes me a suitable engineer. In my local area, I have volunteered and worked at corporations to ameliorate the familiar world around me. I hope to expand this altruism by following my passion in computers, math, and sciences to make a global impact.

Programming is Everywhere, but Procedural Literacy isn’t?

At a career night in my high school, I learned that every career from a biology genome researcher to a home architect uses basic computer programming to expedite some of their daily functions. It might not be advanced to the level of skill of a computer scientist, but a fundamental knowledge/literacy of computers is necessary in education. Therefore, schools should put an emphasis on providing introductory programming classes for students.

Can machines think? – Reflection on Alan Turing’s Paper

“It may be argued that, this being so, one cannot expect to be able to mimic the behaviour of the nervous system with a discrete-state system”

Since a digital computer’s discrete-state system is nothing like the behavior of the nervous system, which does the thinking function for a human, machines would never be able to reach the “thinking” capability of humans unless humans completely redefine and optimize the infrastructure of a machine to create without discrete-state systems and with a more sophisticated system type.

“May not machines carry out something which ought to be described as thinking but which is very different from what a man does? This objection is a very strong one, but at least we can say that if, nevertheless, a machine can be constructed to play the imitation game satisfactorily, we need not be troubled by this objection.”

With the current state and machine type of digital computers, we cannot expect them to have thinking capabilities. Therefore, we should be content with their ability to be “satisfactory” in the imitation game. Machines may  not “think” or have instincts, but we should be happy that they can mimic this behavior in their own way. Machines will remain in the uncanny valley until their infrastructure is optimized into something much more sophisticated.

You may read the rest of his article at: http://www.loebner.net/Prizef/TuringArticle.html

Swarm Algorithm

Swarm algorithm imitates nature, such as swarms of flies or schools of fish. It’s main process is to decentralize organization and have each individual act based on other individuals in its group. This environmental awareness has many implications in artificial intelligence.

For more, see this link: http://en.wikipedia.org/wiki/Swarm_intelligence